Overview

Dataset statistics

Number of variables12
Number of observations8809
Missing cells4329
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory826.0 KiB
Average record size in memory96.0 B

Variable types

Text10
Categorical2

Alerts

rating is highly overall correlated with typeHigh correlation
type is highly overall correlated with ratingHigh correlation
director has 2636 (29.9%) missing valuesMissing
cast has 826 (9.4%) missing valuesMissing
country has 833 (9.5%) missing valuesMissing
show_id has unique valuesUnique

Reproduction

Analysis started2024-03-24 19:37:09.428873
Analysis finished2024-03-24 19:37:10.693617
Duration1.26 second
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

show_id
Text

UNIQUE 

Distinct8809
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-03-24T16:37:10.930410image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length20
Median length5
Mean length4.8772846
Min length2

Characters and Unicode

Total characters42964
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8809 ?
Unique (%)100.0%

Sample

1st rows1
2nd rows2
3rd rows3
4th rows4
5th rows5
ValueCountFrequency (%)
s1 1
 
< 0.1%
s13 1
 
< 0.1%
s19 1
 
< 0.1%
s18 1
 
< 0.1%
s17 1
 
< 0.1%
s16 1
 
< 0.1%
s15 1
 
< 0.1%
s14 1
 
< 0.1%
s12 1
 
< 0.1%
s107 1
 
< 0.1%
Other values (8802) 8802
99.9%
2024-03-24T16:37:11.360626image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8809
20.5%
6 3661
8.5%
1 3661
8.5%
4 3661
8.5%
2 3661
8.5%
3 3661
8.5%
7 3661
8.5%
5 3661
8.5%
8 3376
 
7.9%
9 2560
 
6.0%
Other values (19) 2592
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34121
79.4%
Lowercase Letter 8834
 
20.6%
Space Separator 4
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 8809
99.7%
l 4
 
< 0.1%
r 3
 
< 0.1%
b 2
 
< 0.1%
i 2
 
< 0.1%
y 2
 
< 0.1%
a 2
 
< 0.1%
o 2
 
< 0.1%
n 2
 
< 0.1%
t 1
 
< 0.1%
Other values (5) 5
 
0.1%
Decimal Number
ValueCountFrequency (%)
6 3661
10.7%
1 3661
10.7%
4 3661
10.7%
2 3661
10.7%
3 3661
10.7%
7 3661
10.7%
5 3661
10.7%
8 3376
9.9%
9 2560
7.5%
0 2558
7.5%
Other Punctuation
ValueCountFrequency (%)
" 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34128
79.4%
Latin 8836
 
20.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 8809
99.7%
l 4
 
< 0.1%
r 3
 
< 0.1%
b 2
 
< 0.1%
i 2
 
< 0.1%
y 2
 
< 0.1%
a 2
 
< 0.1%
o 2
 
< 0.1%
n 2
 
< 0.1%
F 2
 
< 0.1%
Other values (6) 6
 
0.1%
Common
ValueCountFrequency (%)
6 3661
10.7%
1 3661
10.7%
4 3661
10.7%
2 3661
10.7%
3 3661
10.7%
7 3661
10.7%
5 3661
10.7%
8 3376
9.9%
9 2560
7.5%
0 2558
7.5%
Other values (3) 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 8809
20.5%
6 3661
8.5%
1 3661
8.5%
4 3661
8.5%
2 3661
8.5%
3 3661
8.5%
7 3661
8.5%
5 3661
8.5%
8 3376
 
7.9%
9 2560
 
6.0%
Other values (19) 2592
 
6.0%

type
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size68.9 KiB
Movie
6131 
TV Show
2676 
William Wyler
 
1

Length

Max length13
Median length5
Mean length5.6085377
Min length5

Characters and Unicode

Total characters49400
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowMovie
2nd rowTV Show
3rd rowTV Show
4th rowTV Show
5th rowTV Show

Common Values

ValueCountFrequency (%)
Movie 6131
69.6%
TV Show 2676
30.4%
William Wyler 1
 
< 0.1%
(Missing) 1
 
< 0.1%

Length

2024-03-24T16:37:11.442336image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-24T16:37:11.489398image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
movie 6131
53.4%
tv 2676
23.3%
show 2676
23.3%
william 1
 
< 0.1%
wyler 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
o 8807
17.8%
i 6133
12.4%
e 6132
12.4%
M 6131
12.4%
v 6131
12.4%
2677
 
5.4%
w 2676
 
5.4%
h 2676
 
5.4%
S 2676
 
5.4%
V 2676
 
5.4%
Other values (7) 2685
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32562
65.9%
Uppercase Letter 14161
28.7%
Space Separator 2677
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 8807
27.0%
i 6133
18.8%
e 6132
18.8%
v 6131
18.8%
w 2676
 
8.2%
h 2676
 
8.2%
l 3
 
< 0.1%
a 1
 
< 0.1%
m 1
 
< 0.1%
y 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
M 6131
43.3%
S 2676
18.9%
V 2676
18.9%
T 2676
18.9%
W 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2677
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46723
94.6%
Common 2677
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 8807
18.8%
i 6133
13.1%
e 6132
13.1%
M 6131
13.1%
v 6131
13.1%
w 2676
 
5.7%
h 2676
 
5.7%
S 2676
 
5.7%
V 2676
 
5.7%
T 2676
 
5.7%
Other values (6) 9
 
< 0.1%
Common
ValueCountFrequency (%)
2677
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 8807
17.8%
i 6133
12.4%
e 6132
12.4%
M 6131
12.4%
v 6131
12.4%
2677
 
5.4%
w 2676
 
5.4%
h 2676
 
5.4%
S 2676
 
5.4%
V 2676
 
5.4%
Other values (7) 2685
 
5.4%

title
Text

Distinct8807
Distinct (%)100.0%
Missing2
Missing (%)< 0.1%
Memory size68.9 KiB
2024-03-24T16:37:11.690444image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length104
Median length71
Mean length17.72397
Min length1

Characters and Unicode

Total characters156095
Distinct characters199
Distinct categories16 ?
Distinct scripts8 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8807 ?
Unique (%)100.0%

Sample

1st rowDick Johnson Is Dead
2nd rowBlood & Water
3rd rowGanglands
4th rowJailbirds New Orleans
5th rowKota Factory
ValueCountFrequency (%)
the 2230
 
8.1%
of 708
 
2.6%
a 354
 
1.3%
in 288
 
1.1%
264
 
1.0%
and 236
 
0.9%
to 199
 
0.7%
love 170
 
0.6%
my 144
 
0.5%
2 129
 
0.5%
Other values (9176) 22673
82.8%
2024-03-24T16:37:11.985817image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18583
 
11.9%
e 14548
 
9.3%
a 11170
 
7.2%
o 8881
 
5.7%
i 8546
 
5.5%
r 8274
 
5.3%
n 8136
 
5.2%
t 7129
 
4.6%
s 6188
 
4.0%
h 5452
 
3.5%
Other values (189) 59188
37.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 108346
69.4%
Uppercase Letter 24998
 
16.0%
Space Separator 18592
 
11.9%
Other Punctuation 2743
 
1.8%
Decimal Number 882
 
0.6%
Dash Punctuation 228
 
0.1%
Other Letter 84
 
0.1%
Open Punctuation 77
 
< 0.1%
Close Punctuation 76
 
< 0.1%
Final Punctuation 38
 
< 0.1%
Other values (6) 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ا 6
 
7.1%
ل 3
 
3.6%
3
 
3.6%
ة 2
 
2.4%
ر 2
 
2.4%
ف 2
 
2.4%
ي 2
 
2.4%
ب 2
 
2.4%
د 2
 
2.4%
و 2
 
2.4%
Other values (52) 58
69.0%
Lowercase Letter
ValueCountFrequency (%)
e 14548
13.4%
a 11170
10.3%
o 8881
 
8.2%
i 8546
 
7.9%
r 8274
 
7.6%
n 8136
 
7.5%
t 7129
 
6.6%
s 6188
 
5.7%
h 5452
 
5.0%
l 5152
 
4.8%
Other values (44) 24870
23.0%
Uppercase Letter
ValueCountFrequency (%)
T 2765
 
11.1%
S 2238
 
9.0%
M 1843
 
7.4%
B 1668
 
6.7%
C 1503
 
6.0%
A 1497
 
6.0%
L 1245
 
5.0%
D 1210
 
4.8%
H 1150
 
4.6%
P 1042
 
4.2%
Other values (26) 8837
35.4%
Other Punctuation
ValueCountFrequency (%)
: 1485
54.1%
' 399
 
14.5%
. 254
 
9.3%
& 179
 
6.5%
, 154
 
5.6%
! 140
 
5.1%
? 58
 
2.1%
* 27
 
1.0%
/ 18
 
0.7%
# 11
 
0.4%
Other values (6) 18
 
0.7%
Decimal Number
ValueCountFrequency (%)
2 233
26.4%
1 143
16.2%
0 138
15.6%
3 85
 
9.6%
9 78
 
8.8%
4 49
 
5.6%
5 43
 
4.9%
6 41
 
4.6%
7 37
 
4.2%
8 35
 
4.0%
Math Symbol
ValueCountFrequency (%)
+ 5
50.0%
| 2
 
20.0%
~ 2
 
20.0%
= 1
 
10.0%
Nonspacing Mark
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Space Separator
ValueCountFrequency (%)
18583
> 99.9%
  9
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 226
99.1%
2
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 76
98.7%
1
 
1.3%
Final Punctuation
ValueCountFrequency (%)
35
92.1%
3
 
7.9%
Initial Punctuation
ValueCountFrequency (%)
2
66.7%
1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Format
ValueCountFrequency (%)
8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 133344
85.4%
Common 22663
 
14.5%
Arabic 33
 
< 0.1%
Hangul 24
 
< 0.1%
Thai 19
 
< 0.1%
Han 6
 
< 0.1%
Katakana 4
 
< 0.1%
Hiragana 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14548
 
10.9%
a 11170
 
8.4%
o 8881
 
6.7%
i 8546
 
6.4%
r 8274
 
6.2%
n 8136
 
6.1%
t 7129
 
5.3%
s 6188
 
4.6%
h 5452
 
4.1%
l 5152
 
3.9%
Other values (80) 49868
37.4%
Common
ValueCountFrequency (%)
18583
82.0%
: 1485
 
6.6%
' 399
 
1.8%
. 254
 
1.1%
2 233
 
1.0%
- 226
 
1.0%
& 179
 
0.8%
, 154
 
0.7%
1 143
 
0.6%
! 140
 
0.6%
Other values (34) 867
 
3.8%
Hangul
ValueCountFrequency (%)
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (13) 13
54.2%
Arabic
ValueCountFrequency (%)
ا 6
18.2%
ل 3
 
9.1%
ة 2
 
6.1%
ر 2
 
6.1%
ف 2
 
6.1%
ي 2
 
6.1%
ب 2
 
6.1%
د 2
 
6.1%
و 2
 
6.1%
م 2
 
6.1%
Other values (7) 8
24.2%
Thai
ValueCountFrequency (%)
3
15.8%
2
10.5%
2
10.5%
2
10.5%
2
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (3) 3
15.8%
Han
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155726
99.8%
None 227
 
0.1%
Punctuation 54
 
< 0.1%
Arabic 33
 
< 0.1%
Hangul 24
 
< 0.1%
Thai 19
 
< 0.1%
CJK 6
 
< 0.1%
Katakana 4
 
< 0.1%
Hiragana 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18583
 
11.9%
e 14548
 
9.3%
a 11170
 
7.2%
o 8881
 
5.7%
i 8546
 
5.5%
r 8274
 
5.3%
n 8136
 
5.2%
t 7129
 
4.6%
s 6188
 
4.0%
h 5452
 
3.5%
Other values (74) 58819
37.8%
None
ValueCountFrequency (%)
é 44
19.4%
í 28
12.3%
ü 19
 
8.4%
ñ 19
 
8.4%
ó 19
 
8.4%
á 18
 
7.9%
  9
 
4.0%
ı 7
 
3.1%
ł 5
 
2.2%
ç 5
 
2.2%
Other values (32) 54
23.8%
Punctuation
ValueCountFrequency (%)
35
64.8%
8
 
14.8%
3
 
5.6%
2
 
3.7%
2
 
3.7%
2
 
3.7%
1
 
1.9%
1
 
1.9%
Arabic
ValueCountFrequency (%)
ا 6
18.2%
ل 3
 
9.1%
ة 2
 
6.1%
ر 2
 
6.1%
ف 2
 
6.1%
ي 2
 
6.1%
ب 2
 
6.1%
د 2
 
6.1%
و 2
 
6.1%
م 2
 
6.1%
Other values (7) 8
24.2%
Thai
ValueCountFrequency (%)
3
15.8%
2
10.5%
2
10.5%
2
10.5%
2
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (3) 3
15.8%
Hangul
ValueCountFrequency (%)
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (13) 13
54.2%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
CJK
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

director
Text

MISSING 

Distinct4528
Distinct (%)73.4%
Missing2636
Missing (%)29.9%
Memory size68.9 KiB
2024-03-24T16:37:12.202411image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length208
Median length167
Mean length15.372266
Min length2

Characters and Unicode

Total characters94893
Distinct characters106
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3661 ?
Unique (%)59.3%

Sample

1st rowKirsten Johnson
2nd rowJulien Leclercq
3rd rowMike Flanagan
4th rowRobert Cullen, José Luis Ucha
5th rowHaile Gerima
ValueCountFrequency (%)
david 122
 
0.8%
michael 117
 
0.8%
john 90
 
0.6%
paul 74
 
0.5%
robert 56
 
0.4%
peter 52
 
0.4%
chris 52
 
0.4%
daniel 49
 
0.3%
james 48
 
0.3%
mike 44
 
0.3%
Other values (6503) 13987
95.2%
2024-03-24T16:37:12.473141image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10128
 
10.7%
8518
 
9.0%
e 7050
 
7.4%
n 6235
 
6.6%
i 5918
 
6.2%
r 5609
 
5.9%
o 4930
 
5.2%
l 3880
 
4.1%
h 3302
 
3.5%
s 3096
 
3.3%
Other values (96) 36227
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 69999
73.8%
Uppercase Letter 14984
 
15.8%
Space Separator 8518
 
9.0%
Other Punctuation 1184
 
1.2%
Dash Punctuation 205
 
0.2%
Final Punctuation 2
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 10128
14.5%
e 7050
10.1%
n 6235
 
8.9%
i 5918
 
8.5%
r 5609
 
8.0%
o 4930
 
7.0%
l 3880
 
5.5%
h 3302
 
4.7%
s 3096
 
4.4%
t 2982
 
4.3%
Other values (48) 16869
24.1%
Uppercase Letter
ValueCountFrequency (%)
S 1580
 
10.5%
M 1431
 
9.6%
A 1172
 
7.8%
J 982
 
6.6%
R 954
 
6.4%
B 911
 
6.1%
C 893
 
6.0%
D 763
 
5.1%
K 758
 
5.1%
P 663
 
4.4%
Other values (28) 4877
32.5%
Other Punctuation
ValueCountFrequency (%)
, 805
68.0%
. 339
28.6%
' 35
 
3.0%
" 2
 
0.2%
& 2
 
0.2%
! 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 84983
89.6%
Common 9910
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 10128
 
11.9%
e 7050
 
8.3%
n 6235
 
7.3%
i 5918
 
7.0%
r 5609
 
6.6%
o 4930
 
5.8%
l 3880
 
4.6%
h 3302
 
3.9%
s 3096
 
3.6%
t 2982
 
3.5%
Other values (86) 31853
37.5%
Common
ValueCountFrequency (%)
8518
86.0%
, 805
 
8.1%
. 339
 
3.4%
- 205
 
2.1%
' 35
 
0.4%
" 2
 
< 0.1%
& 2
 
< 0.1%
2
 
< 0.1%
9 1
 
< 0.1%
! 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94421
99.5%
None 470
 
0.5%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 10128
 
10.7%
8518
 
9.0%
e 7050
 
7.5%
n 6235
 
6.6%
i 5918
 
6.3%
r 5609
 
5.9%
o 4930
 
5.2%
l 3880
 
4.1%
h 3302
 
3.5%
s 3096
 
3.3%
Other values (51) 35755
37.9%
None
ValueCountFrequency (%)
á 65
13.8%
é 60
12.8%
ó 42
8.9%
ı 40
8.5%
í 40
8.5%
ü 34
 
7.2%
ö 27
 
5.7%
ú 25
 
5.3%
ç 23
 
4.9%
ğ 15
 
3.2%
Other values (34) 99
21.1%
Punctuation
ValueCountFrequency (%)
2
100.0%

cast
Text

MISSING 

Distinct7693
Distinct (%)96.4%
Missing826
Missing (%)9.4%
Memory size68.9 KiB
2024-03-24T16:37:12.756800image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length771
Median length357
Mean length119.74045
Min length3

Characters and Unicode

Total characters955888
Distinct characters156
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7527 ?
Unique (%)94.3%

Sample

1st rowAma Qamata, Khosi Ngema, Gail Mabalane, Thabang Molaba, Dillon Windvogel, Natasha Thahane, Arno Greeff, Xolile Tshabalala, Getmore Sithole, Cindy Mahlangu, Ryle De Morny, Greteli Fincham, Sello Maake Ka-Ncube, Odwa Gwanya, Mekaila Mathys, Sandi Schultz, Duane Williams, Shamilla Miller, Patrick Mofokeng
2nd rowSami Bouajila, Tracy Gotoas, Samuel Jouy, Nabiha Akkari, Sofia Lesaffre, Salim Kechiouche, Noureddine Farihi, Geert Van Rampelberg, Bakary Diombera
3rd rowMayur More, Jitendra Kumar, Ranjan Raj, Alam Khan, Ahsaas Channa, Revathi Pillai, Urvi Singh, Arun Kumar
4th rowKate Siegel, Zach Gilford, Hamish Linklater, Henry Thomas, Kristin Lehman, Samantha Sloyan, Igby Rigney, Rahul Kohli, Annarah Cymone, Annabeth Gish, Alex Essoe, Rahul Abburi, Matt Biedel, Michael Trucco, Crystal Balint, Louis Oliver
5th rowVanessa Hudgens, Kimiko Glenn, James Marsden, Sofia Carson, Liza Koshy, Ken Jeong, Elizabeth Perkins, Jane Krakowski, Michael McKean, Phil LaMarr
ValueCountFrequency (%)
michael 650
 
0.5%
david 562
 
0.4%
john 558
 
0.4%
lee 459
 
0.3%
james 419
 
0.3%
kim 350
 
0.3%
paul 345
 
0.3%
de 288
 
0.2%
khan 263
 
0.2%
chris 252
 
0.2%
Other values (33192) 127909
96.9%
2024-03-24T16:37:13.104614image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124079
 
13.0%
a 95017
 
9.9%
e 65743
 
6.9%
n 57634
 
6.0%
i 56520
 
5.9%
, 56145
 
5.9%
r 48398
 
5.1%
o 44553
 
4.7%
l 35351
 
3.7%
h 28543
 
3.0%
Other values (146) 343905
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 636726
66.6%
Uppercase Letter 134485
 
14.1%
Space Separator 124079
 
13.0%
Other Punctuation 57748
 
6.0%
Dash Punctuation 2773
 
0.3%
Decimal Number 45
 
< 0.1%
Final Punctuation 12
 
< 0.1%
Nonspacing Mark 8
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Other values (4) 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 95017
14.9%
e 65743
10.3%
n 57634
 
9.1%
i 56520
 
8.9%
r 48398
 
7.6%
o 44553
 
7.0%
l 35351
 
5.6%
h 28543
 
4.5%
s 27877
 
4.4%
t 25724
 
4.0%
Other values (67) 151366
23.8%
Uppercase Letter
ValueCountFrequency (%)
S 12963
 
9.6%
M 11957
 
8.9%
A 10228
 
7.6%
J 8516
 
6.3%
C 8487
 
6.3%
B 7946
 
5.9%
K 7888
 
5.9%
R 7169
 
5.3%
D 6905
 
5.1%
L 5953
 
4.4%
Other values (38) 46473
34.6%
Decimal Number
ValueCountFrequency (%)
0 9
20.0%
4 7
15.6%
2 6
13.3%
8 6
13.3%
1 5
11.1%
5 5
11.1%
7 2
 
4.4%
9 2
 
4.4%
3 2
 
4.4%
6 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 56145
97.2%
. 1116
 
1.9%
' 403
 
0.7%
" 57
 
0.1%
20
 
< 0.1%
& 5
 
< 0.1%
! 2
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
́ 5
62.5%
2
 
25.0%
1
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 2770
99.9%
3
 
0.1%
Final Punctuation
ValueCountFrequency (%)
10
83.3%
2
 
16.7%
Space Separator
ValueCountFrequency (%)
124079
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Format
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 771211
80.7%
Common 184669
 
19.3%
Inherited 7
 
< 0.1%
Thai 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 95017
 
12.3%
e 65743
 
8.5%
n 57634
 
7.5%
i 56520
 
7.3%
r 48398
 
6.3%
o 44553
 
5.8%
l 35351
 
4.6%
h 28543
 
3.7%
s 27877
 
3.6%
t 25724
 
3.3%
Other values (115) 285851
37.1%
Common
ValueCountFrequency (%)
124079
67.2%
, 56145
30.4%
- 2770
 
1.5%
. 1116
 
0.6%
' 403
 
0.2%
" 57
 
< 0.1%
20
 
< 0.1%
10
 
< 0.1%
0 9
 
< 0.1%
4 7
 
< 0.1%
Other values (18) 53
 
< 0.1%
Inherited
ValueCountFrequency (%)
́ 5
71.4%
2
 
28.6%
Thai
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 951306
99.5%
None 4534
 
0.5%
Katakana 20
 
< 0.1%
Punctuation 17
 
< 0.1%
Diacriticals 5
 
< 0.1%
Latin Ext Additional 3
 
< 0.1%
VS 2
 
< 0.1%
Thai 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124079
 
13.0%
a 95017
 
10.0%
e 65743
 
6.9%
n 57634
 
6.1%
i 56520
 
5.9%
, 56145
 
5.9%
r 48398
 
5.1%
o 44553
 
4.7%
l 35351
 
3.7%
h 28543
 
3.0%
Other values (64) 339323
35.7%
None
ValueCountFrequency (%)
é 769
17.0%
á 637
14.0%
í 535
11.8%
ó 334
 
7.4%
ü 320
 
7.1%
ı 225
 
5.0%
ñ 159
 
3.5%
ç 155
 
3.4%
ğ 138
 
3.0%
ö 130
 
2.9%
Other values (60) 1132
25.0%
Katakana
ValueCountFrequency (%)
20
100.0%
Punctuation
ValueCountFrequency (%)
10
58.8%
3
 
17.6%
2
 
11.8%
1
 
5.9%
1
 
5.9%
Diacriticals
ValueCountFrequency (%)
́ 5
100.0%
VS
ValueCountFrequency (%)
2
100.0%
Latin Ext Additional
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Thai
ValueCountFrequency (%)
1
100.0%

country
Text

MISSING 

Distinct749
Distinct (%)9.4%
Missing833
Missing (%)9.5%
Memory size68.9 KiB
2024-03-24T16:37:13.291736image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length123
Median length104
Mean length12.579238
Min length4

Characters and Unicode

Total characters100332
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique564 ?
Unique (%)7.1%

Sample

1st rowUnited States
2nd rowSouth Africa
3rd rowIndia
4th rowUnited States, Ghana, Burkina Faso, United Kingdom, Germany, Ethiopia
5th rowUnited Kingdom
ValueCountFrequency (%)
united 4532
30.1%
states 3689
24.5%
india 1046
 
6.9%
kingdom 806
 
5.4%
canada 445
 
3.0%
france 393
 
2.6%
japan 318
 
2.1%
south 293
 
1.9%
germany 232
 
1.5%
spain 232
 
1.5%
Other values (127) 3079
20.4%
2024-03-24T16:37:13.536917image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 12877
12.8%
e 10540
10.5%
a 10181
10.1%
n 9526
9.5%
i 8591
8.6%
d 7280
 
7.3%
7089
 
7.1%
U 4553
 
4.5%
S 4353
 
4.3%
s 4280
 
4.3%
Other values (44) 21062
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 76134
75.9%
Uppercase Letter 15062
 
15.0%
Space Separator 7089
 
7.1%
Other Punctuation 2043
 
2.0%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 12877
16.9%
e 10540
13.8%
a 10181
13.4%
n 9526
12.5%
i 8591
11.3%
d 7280
9.6%
s 4280
 
5.6%
o 2144
 
2.8%
r 1987
 
2.6%
g 1530
 
2.0%
Other values (16) 7198
9.5%
Uppercase Letter
ValueCountFrequency (%)
U 4553
30.2%
S 4353
28.9%
I 1331
 
8.8%
K 1157
 
7.7%
C 726
 
4.8%
F 405
 
2.7%
A 383
 
2.5%
J 328
 
2.2%
T 272
 
1.8%
G 252
 
1.7%
Other values (13) 1302
 
8.6%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
1 1
25.0%
9 1
25.0%
Space Separator
ValueCountFrequency (%)
7089
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2043
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91196
90.9%
Common 9136
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 12877
14.1%
e 10540
11.6%
a 10181
11.2%
n 9526
10.4%
i 8591
9.4%
d 7280
8.0%
U 4553
 
5.0%
S 4353
 
4.8%
s 4280
 
4.7%
o 2144
 
2.4%
Other values (39) 16871
18.5%
Common
ValueCountFrequency (%)
7089
77.6%
, 2043
 
22.4%
4 2
 
< 0.1%
1 1
 
< 0.1%
9 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 12877
12.8%
e 10540
10.5%
a 10181
10.1%
n 9526
9.5%
i 8591
8.6%
d 7280
 
7.3%
7089
 
7.1%
U 4553
 
4.5%
S 4353
 
4.3%
s 4280
 
4.3%
Other values (44) 21062
21.0%
Distinct1768
Distinct (%)20.1%
Missing12
Missing (%)0.1%
Memory size68.9 KiB
2024-03-24T16:37:13.673192image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.737524
Min length5

Characters and Unicode

Total characters129646
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique548 ?
Unique (%)6.2%

Sample

1st rowSeptember 25, 2021
2nd rowSeptember 24, 2021
3rd rowSeptember 24, 2021
4th rowSeptember 24, 2021
5th rowSeptember 24, 2021
ValueCountFrequency (%)
1 2212
 
8.4%
2019 2016
 
7.6%
2020 1879
 
7.1%
2018 1649
 
6.2%
2021 1498
 
5.7%
2017 1187
 
4.5%
july 827
 
3.1%
december 813
 
3.1%
september 770
 
2.9%
april 764
 
2.9%
Other values (48) 12774
48.4%
2024-03-24T16:37:13.852659image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17680
13.6%
2 14856
 
11.5%
1 12276
 
9.5%
0 11353
 
8.8%
, 8796
 
6.8%
e 8210
 
6.3%
r 6417
 
4.9%
u 4366
 
3.4%
b 3611
 
2.8%
a 3412
 
2.6%
Other values (33) 38669
29.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48930
37.7%
Lowercase Letter 45439
35.0%
Space Separator 17680
 
13.6%
Uppercase Letter 8800
 
6.8%
Other Punctuation 8796
 
6.8%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8210
18.1%
r 6417
14.1%
u 4366
9.6%
b 3611
7.9%
a 3412
7.5%
y 2760
 
6.1%
c 2314
 
5.1%
m 2288
 
5.0%
t 2285
 
5.0%
l 1591
 
3.5%
Other values (8) 8185
18.0%
Uppercase Letter
ValueCountFrequency (%)
J 2293
26.1%
A 1519
17.3%
M 1373
15.6%
D 813
 
9.2%
S 770
 
8.8%
O 760
 
8.6%
N 705
 
8.0%
F 563
 
6.4%
T 1
 
< 0.1%
V 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 14856
30.4%
1 12276
25.1%
0 11353
23.2%
9 2549
 
5.2%
8 2249
 
4.6%
7 1756
 
3.6%
5 1197
 
2.4%
6 1134
 
2.3%
3 1004
 
2.1%
4 556
 
1.1%
Space Separator
ValueCountFrequency (%)
17680
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8796
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75407
58.2%
Latin 54239
41.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8210
15.1%
r 6417
 
11.8%
u 4366
 
8.0%
b 3611
 
6.7%
a 3412
 
6.3%
y 2760
 
5.1%
c 2314
 
4.3%
J 2293
 
4.2%
m 2288
 
4.2%
t 2285
 
4.2%
Other values (20) 16283
30.0%
Common
ValueCountFrequency (%)
17680
23.4%
2 14856
19.7%
1 12276
16.3%
0 11353
15.1%
, 8796
11.7%
9 2549
 
3.4%
8 2249
 
3.0%
7 1756
 
2.3%
5 1197
 
1.6%
6 1134
 
1.5%
Other values (3) 1561
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129646
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17680
13.6%
2 14856
 
11.5%
1 12276
 
9.5%
0 11353
 
8.8%
, 8796
 
6.8%
e 8210
 
6.3%
r 6417
 
4.9%
u 4366
 
3.4%
b 3611
 
2.8%
a 3412
 
2.6%
Other values (33) 38669
29.8%
Distinct75
Distinct (%)0.9%
Missing2
Missing (%)< 0.1%
Memory size68.9 KiB
2024-03-24T16:37:13.984777image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0002271
Min length4

Characters and Unicode

Total characters35230
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row2020
2nd row2021
3rd row2021
4th row2021
5th row2021
ValueCountFrequency (%)
2018 1147
13.0%
2017 1032
11.7%
2019 1030
11.7%
2020 953
10.8%
2016 902
10.2%
2021 592
 
6.7%
2015 560
 
6.4%
2014 352
 
4.0%
2013 288
 
3.3%
2012 237
 
2.7%
Other values (66) 1715
19.5%
2024-03-24T16:37:14.167583image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10316
29.3%
2 10166
28.9%
1 7309
20.7%
9 2049
 
5.8%
8 1479
 
4.2%
7 1249
 
3.5%
6 1074
 
3.0%
5 703
 
2.0%
4 478
 
1.4%
3 403
 
1.1%
Other values (4) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35226
> 99.9%
Lowercase Letter 3
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10316
29.3%
2 10166
28.9%
1 7309
20.7%
9 2049
 
5.8%
8 1479
 
4.2%
7 1249
 
3.5%
6 1074
 
3.0%
5 703
 
2.0%
4 478
 
1.4%
3 403
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
m 1
33.3%
i 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35227
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10316
29.3%
2 10166
28.9%
1 7309
20.7%
9 2049
 
5.8%
8 1479
 
4.2%
7 1249
 
3.5%
6 1074
 
3.0%
5 703
 
2.0%
4 478
 
1.4%
3 403
 
1.1%
Latin
ValueCountFrequency (%)
m 1
33.3%
i 1
33.3%
n 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10316
29.3%
2 10166
28.9%
1 7309
20.7%
9 2049
 
5.8%
8 1479
 
4.2%
7 1249
 
3.5%
6 1074
 
3.0%
5 703
 
2.0%
4 478
 
1.4%
3 403
 
1.1%
Other values (4) 4
 
< 0.1%

rating
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing6
Missing (%)0.1%
Memory size68.9 KiB
TV-MA
3207 
TV-14
2160 
TV-PG
862 
R
799 
PG-13
490 
Other values (13)
1285 

Length

Max length29
Median length5
Mean length4.4374645
Min length1

Characters and Unicode

Total characters39063
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowPG-13
2nd rowTV-MA
3rd rowTV-MA
4th rowTV-MA
5th rowTV-MA

Common Values

ValueCountFrequency (%)
TV-MA 3207
36.4%
TV-14 2160
24.5%
TV-PG 862
 
9.8%
R 799
 
9.1%
PG-13 490
 
5.6%
TV-Y7 334
 
3.8%
TV-Y 307
 
3.5%
PG 287
 
3.3%
TV-G 220
 
2.5%
NR 80
 
0.9%
Other values (8) 57
 
0.6%

Length

2024-03-24T16:37:14.239138image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv-ma 3207
36.4%
tv-14 2160
24.5%
tv-pg 862
 
9.8%
r 799
 
9.1%
pg-13 490
 
5.6%
tv-y7 334
 
3.8%
tv-y 307
 
3.5%
pg 287
 
3.3%
tv-g 220
 
2.5%
nr 80
 
0.9%
Other values (11) 62
 
0.7%

Most occurring characters

ValueCountFrequency (%)
- 7595
19.4%
V 7102
18.2%
T 7096
18.2%
M 3208
8.2%
A 3207
8.2%
1 2653
 
6.8%
4 2162
 
5.5%
G 1900
 
4.9%
P 1639
 
4.2%
R 882
 
2.3%
Other values (25) 1619
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 25778
66.0%
Dash Punctuation 7595
 
19.4%
Decimal Number 5652
 
14.5%
Lowercase Letter 32
 
0.1%
Space Separator 5
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
V 7102
27.6%
T 7096
27.5%
M 3208
12.4%
A 3207
12.4%
G 1900
 
7.4%
P 1639
 
6.4%
R 882
 
3.4%
Y 647
 
2.5%
N 83
 
0.3%
F 6
 
< 0.1%
Other values (3) 8
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
i 6
18.8%
s 4
12.5%
n 4
12.5%
m 4
12.5%
e 3
9.4%
o 2
 
6.2%
c 2
 
6.2%
a 2
 
6.2%
l 1
 
3.1%
v 1
 
3.1%
Other values (3) 3
9.4%
Decimal Number
ValueCountFrequency (%)
1 2653
46.9%
4 2162
38.3%
3 490
 
8.7%
7 344
 
6.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 7595
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25810
66.1%
Common 13253
33.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
V 7102
27.5%
T 7096
27.5%
M 3208
12.4%
A 3207
12.4%
G 1900
 
7.4%
P 1639
 
6.4%
R 882
 
3.4%
Y 647
 
2.5%
N 83
 
0.3%
F 6
 
< 0.1%
Other values (16) 40
 
0.2%
Common
ValueCountFrequency (%)
- 7595
57.3%
1 2653
 
20.0%
4 2162
 
16.3%
3 490
 
3.7%
7 344
 
2.6%
5
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
, 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39063
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7595
19.4%
V 7102
18.2%
T 7096
18.2%
M 3208
8.2%
A 3207
8.2%
1 2653
 
6.8%
4 2162
 
5.5%
G 1900
 
4.9%
P 1639
 
4.2%
R 882
 
2.3%
Other values (25) 1619
 
4.1%
Distinct221
Distinct (%)2.5%
Missing5
Missing (%)0.1%
Memory size68.9 KiB
2024-03-24T16:37:14.408681image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length146
Median length10
Mean length7.0574739
Min length5

Characters and Unicode

Total characters62134
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)0.4%

Sample

1st row90 min
2nd row2 Seasons
3rd row1 Season
4th row1 Season
5th row2 Seasons
ValueCountFrequency (%)
min 6127
34.8%
1 1793
 
10.2%
season 1793
 
10.2%
seasons 883
 
5.0%
2 425
 
2.4%
3 200
 
1.1%
90 152
 
0.9%
97 146
 
0.8%
93 146
 
0.8%
94 146
 
0.8%
Other values (226) 5819
33.0%
2024-03-24T16:37:14.652741image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8826
14.2%
n 8810
14.2%
i 6135
9.9%
m 6132
9.9%
1 6049
9.7%
s 3569
 
5.7%
e 2694
 
4.3%
o 2684
 
4.3%
a 2682
 
4.3%
S 2676
 
4.3%
Other values (31) 11877
19.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32756
52.7%
Decimal Number 17867
28.8%
Space Separator 8826
 
14.2%
Uppercase Letter 2683
 
4.3%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 8810
26.9%
i 6135
18.7%
m 6132
18.7%
s 3569
10.9%
e 2694
 
8.2%
o 2684
 
8.2%
a 2682
 
8.2%
r 10
 
< 0.1%
t 10
 
< 0.1%
c 5
 
< 0.1%
Other values (12) 25
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 6049
33.9%
9 1939
 
10.9%
0 1689
 
9.5%
2 1615
 
9.0%
8 1435
 
8.0%
3 1216
 
6.8%
6 1006
 
5.6%
7 993
 
5.6%
4 973
 
5.4%
5 952
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 2676
99.7%
F 2
 
0.1%
B 2
 
0.1%
M 1
 
< 0.1%
T 1
 
< 0.1%
G 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
8826
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35439
57.0%
Common 26695
43.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 8810
24.9%
i 6135
17.3%
m 6132
17.3%
s 3569
10.1%
e 2694
 
7.6%
o 2684
 
7.6%
a 2682
 
7.6%
S 2676
 
7.6%
r 10
 
< 0.1%
t 10
 
< 0.1%
Other values (18) 37
 
0.1%
Common
ValueCountFrequency (%)
8826
33.1%
1 6049
22.7%
9 1939
 
7.3%
0 1689
 
6.3%
2 1615
 
6.0%
8 1435
 
5.4%
3 1216
 
4.6%
6 1006
 
3.8%
7 993
 
3.7%
4 973
 
3.6%
Other values (3) 954
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8826
14.2%
n 8810
14.2%
i 6135
9.9%
m 6132
9.9%
1 6049
9.7%
s 3569
 
5.7%
e 2694
 
4.3%
o 2684
 
4.3%
a 2682
 
4.3%
S 2676
 
4.3%
Other values (31) 11877
19.1%
Distinct514
Distinct (%)5.8%
Missing3
Missing (%)< 0.1%
Memory size68.9 KiB
2024-03-24T16:37:14.804700image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length79
Median length58
Mean length33.406314
Min length6

Characters and Unicode

Total characters294176
Distinct characters43
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)1.6%

Sample

1st rowDocumentaries
2nd rowInternational TV Shows, TV Dramas, TV Mysteries
3rd rowCrime TV Shows, International TV Shows, TV Action & Adventure
4th rowDocuseries, Reality TV
5th rowInternational TV Shows, Romantic TV Shows, TV Comedies
ValueCountFrequency (%)
movies 5686
14.5%
tv 5506
14.0%
international 4103
10.5%
dramas 3190
 
8.1%
shows 2910
 
7.4%
2611
 
6.7%
comedies 2255
 
5.7%
action 1027
 
2.6%
adventure 1027
 
2.6%
romantic 986
 
2.5%
Other values (33) 9917
25.3%
2024-03-24T16:37:15.017290image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30412
 
10.3%
e 25222
 
8.6%
i 21512
 
7.3%
n 20759
 
7.1%
a 19929
 
6.8%
o 19863
 
6.8%
s 19611
 
6.7%
t 14878
 
5.1%
r 14383
 
4.9%
, 10515
 
3.6%
Other values (33) 97092
33.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 205866
70.0%
Uppercase Letter 43421
 
14.8%
Space Separator 30412
 
10.3%
Other Punctuation 13577
 
4.6%
Dash Punctuation 900
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 25222
12.3%
i 21512
10.4%
n 20759
10.1%
a 19929
9.7%
o 19863
9.6%
s 19611
9.5%
t 14878
7.2%
r 14383
7.0%
m 9056
 
4.4%
l 7646
 
3.7%
Other values (10) 33007
16.0%
Uppercase Letter
ValueCountFrequency (%)
M 6534
15.0%
T 6367
14.7%
V 5506
12.7%
I 4859
11.2%
D 4453
10.3%
S 4362
10.0%
C 4007
9.2%
A 2301
 
5.3%
F 1431
 
3.3%
R 1241
 
2.9%
Other values (8) 2360
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 10515
77.4%
& 2611
 
19.2%
' 451
 
3.3%
Space Separator
ValueCountFrequency (%)
30412
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 900
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 249287
84.7%
Common 44889
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 25222
 
10.1%
i 21512
 
8.6%
n 20759
 
8.3%
a 19929
 
8.0%
o 19863
 
8.0%
s 19611
 
7.9%
t 14878
 
6.0%
r 14383
 
5.8%
m 9056
 
3.6%
l 7646
 
3.1%
Other values (28) 76428
30.7%
Common
ValueCountFrequency (%)
30412
67.7%
, 10515
 
23.4%
& 2611
 
5.8%
- 900
 
2.0%
' 451
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 294176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30412
 
10.3%
e 25222
 
8.6%
i 21512
 
7.3%
n 20759
 
7.1%
a 19929
 
6.8%
o 19863
 
6.8%
s 19611
 
6.7%
t 14878
 
5.1%
r 14383
 
4.9%
, 10515
 
3.6%
Other values (33) 97092
33.0%
Distinct8774
Distinct (%)99.6%
Missing3
Missing (%)< 0.1%
Memory size68.9 KiB
2024-03-24T16:37:15.246813image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length248
Median length240
Mean length143.24143
Min length26

Characters and Unicode

Total characters1261384
Distinct characters126
Distinct categories16 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8747 ?
Unique (%)99.3%

Sample

1st rowAs her father nears the end of his life, filmmaker Kirsten Johnson stages his death in inventive and comical ways to help them both face the inevitable.
2nd rowAfter crossing paths at a party, a Cape Town teen sets out to prove whether a private-school swimming star is her sister who was abducted at birth.
3rd rowTo protect his family from a powerful drug lord, skilled thief Mehdi and his expert team of robbers are pulled into a violent and deadly turf war.
4th rowFeuds, flirtations and toilet talk go down among the incarcerated women at the Orleans Justice Center in New Orleans on this gritty reality series.
5th rowIn a city of coaching centers known to train India’s finest collegiate minds, an earnest but unexceptional student and his friends navigate campus life.
ValueCountFrequency (%)
a 11609
 
5.5%
the 8135
 
3.9%
to 6440
 
3.1%
and 6333
 
3.0%
of 5274
 
2.5%
in 4353
 
2.1%
his 3355
 
1.6%
with 2268
 
1.1%
her 2166
 
1.0%
an 1993
 
0.9%
Other values (21452) 158290
75.3%
2024-03-24T16:37:15.539710image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
201406
16.0%
e 118629
 
9.4%
a 84732
 
6.7%
t 81313
 
6.4%
i 78372
 
6.2%
n 74509
 
5.9%
o 72656
 
5.8%
s 72600
 
5.8%
r 70742
 
5.6%
h 48498
 
3.8%
Other values (116) 357927
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1002706
79.5%
Space Separator 201416
 
16.0%
Uppercase Letter 26446
 
2.1%
Other Punctuation 22479
 
1.8%
Dash Punctuation 4521
 
0.4%
Decimal Number 3171
 
0.3%
Final Punctuation 516
 
< 0.1%
Initial Punctuation 37
 
< 0.1%
Currency Symbol 34
 
< 0.1%
Close Punctuation 24
 
< 0.1%
Other values (6) 34
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 118629
11.8%
a 84732
 
8.5%
t 81313
 
8.1%
i 78372
 
7.8%
n 74509
 
7.4%
o 72656
 
7.2%
s 72600
 
7.2%
r 70742
 
7.1%
h 48498
 
4.8%
l 41638
 
4.2%
Other values (45) 259017
25.8%
Uppercase Letter
ValueCountFrequency (%)
A 4102
15.5%
T 2209
 
8.4%
S 1870
 
7.1%
B 1667
 
6.3%
W 1643
 
6.2%
I 1583
 
6.0%
C 1553
 
5.9%
M 1395
 
5.3%
F 1046
 
4.0%
D 919
 
3.5%
Other values (22) 8459
32.0%
Other Punctuation
ValueCountFrequency (%)
. 9961
44.3%
, 8912
39.6%
' 2506
 
11.1%
" 702
 
3.1%
: 140
 
0.6%
! 133
 
0.6%
? 100
 
0.4%
/ 11
 
< 0.1%
& 8
 
< 0.1%
3
 
< 0.1%
Other values (2) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 759
23.9%
1 754
23.8%
9 461
14.5%
2 308
9.7%
8 177
 
5.6%
5 166
 
5.2%
6 140
 
4.4%
3 138
 
4.4%
7 137
 
4.3%
4 131
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 3632
80.3%
605
 
13.4%
284
 
6.3%
Space Separator
ValueCountFrequency (%)
201406
> 99.9%
  10
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
478
92.6%
38
 
7.4%
Initial Punctuation
ValueCountFrequency (%)
34
91.9%
3
 
8.1%
Currency Symbol
ValueCountFrequency (%)
$ 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Other Letter
ValueCountFrequency (%)
º 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 2
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1029157
81.6%
Common 232227
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 118629
11.5%
a 84732
 
8.2%
t 81313
 
7.9%
i 78372
 
7.6%
n 74509
 
7.2%
o 72656
 
7.1%
s 72600
 
7.1%
r 70742
 
6.9%
h 48498
 
4.7%
l 41638
 
4.0%
Other values (78) 285468
27.7%
Common
ValueCountFrequency (%)
201406
86.7%
. 9961
 
4.3%
, 8912
 
3.8%
- 3632
 
1.6%
' 2506
 
1.1%
0 759
 
0.3%
1 754
 
0.3%
" 702
 
0.3%
605
 
0.3%
478
 
0.2%
Other values (28) 2512
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1259634
99.9%
Punctuation 1445
 
0.1%
None 304
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
201406
16.0%
e 118629
 
9.4%
a 84732
 
6.7%
t 81313
 
6.5%
i 78372
 
6.2%
n 74509
 
5.9%
o 72656
 
5.8%
s 72600
 
5.8%
r 70742
 
5.6%
h 48498
 
3.9%
Other values (69) 356177
28.3%
Punctuation
ValueCountFrequency (%)
605
41.9%
478
33.1%
284
19.7%
38
 
2.6%
34
 
2.4%
3
 
0.2%
3
 
0.2%
None
ValueCountFrequency (%)
é 100
32.9%
á 47
15.5%
í 32
 
10.5%
ó 16
 
5.3%
ñ 11
 
3.6%
ü 11
 
3.6%
  10
 
3.3%
ï 9
 
3.0%
ã 8
 
2.6%
ł 6
 
2.0%
Other values (29) 54
17.8%
Modifier Letters
ValueCountFrequency (%)
ʻ 1
100.0%

Correlations

2024-03-24T16:37:15.596875image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ratingtype
rating1.0000.747
type0.7471.000

Missing values

2024-03-24T16:37:10.420243image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-24T16:37:10.554959image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

show_idtypetitledirectorcastcountrydate_addedrelease_yearratingdurationlisted_indescription
0s1MovieDick Johnson Is DeadKirsten JohnsonNaNUnited StatesSeptember 25, 20212020PG-1390 minDocumentariesAs her father nears the end of his life, filmmaker Kirsten Johnson stages his death in inventive and comical ways to help them both face the inevitable.
1s2TV ShowBlood & WaterNaNAma Qamata, Khosi Ngema, Gail Mabalane, Thabang Molaba, Dillon Windvogel, Natasha Thahane, Arno Greeff, Xolile Tshabalala, Getmore Sithole, Cindy Mahlangu, Ryle De Morny, Greteli Fincham, Sello Maake Ka-Ncube, Odwa Gwanya, Mekaila Mathys, Sandi Schultz, Duane Williams, Shamilla Miller, Patrick MofokengSouth AfricaSeptember 24, 20212021TV-MA2 SeasonsInternational TV Shows, TV Dramas, TV MysteriesAfter crossing paths at a party, a Cape Town teen sets out to prove whether a private-school swimming star is her sister who was abducted at birth.
2s3TV ShowGanglandsJulien LeclercqSami Bouajila, Tracy Gotoas, Samuel Jouy, Nabiha Akkari, Sofia Lesaffre, Salim Kechiouche, Noureddine Farihi, Geert Van Rampelberg, Bakary DiomberaNaNSeptember 24, 20212021TV-MA1 SeasonCrime TV Shows, International TV Shows, TV Action & AdventureTo protect his family from a powerful drug lord, skilled thief Mehdi and his expert team of robbers are pulled into a violent and deadly turf war.
3s4TV ShowJailbirds New OrleansNaNNaNNaNSeptember 24, 20212021TV-MA1 SeasonDocuseries, Reality TVFeuds, flirtations and toilet talk go down among the incarcerated women at the Orleans Justice Center in New Orleans on this gritty reality series.
4s5TV ShowKota FactoryNaNMayur More, Jitendra Kumar, Ranjan Raj, Alam Khan, Ahsaas Channa, Revathi Pillai, Urvi Singh, Arun KumarIndiaSeptember 24, 20212021TV-MA2 SeasonsInternational TV Shows, Romantic TV Shows, TV ComediesIn a city of coaching centers known to train India’s finest collegiate minds, an earnest but unexceptional student and his friends navigate campus life.
5s6TV ShowMidnight MassMike FlanaganKate Siegel, Zach Gilford, Hamish Linklater, Henry Thomas, Kristin Lehman, Samantha Sloyan, Igby Rigney, Rahul Kohli, Annarah Cymone, Annabeth Gish, Alex Essoe, Rahul Abburi, Matt Biedel, Michael Trucco, Crystal Balint, Louis OliverNaNSeptember 24, 20212021TV-MA1 SeasonTV Dramas, TV Horror, TV MysteriesThe arrival of a charismatic young priest brings glorious miracles, ominous mysteries and renewed religious fervor to a dying town desperate to believe.
6s7MovieMy Little Pony: A New GenerationRobert Cullen, José Luis UchaVanessa Hudgens, Kimiko Glenn, James Marsden, Sofia Carson, Liza Koshy, Ken Jeong, Elizabeth Perkins, Jane Krakowski, Michael McKean, Phil LaMarrNaNSeptember 24, 20212021PG91 minChildren & Family MoviesEquestria's divided. But a bright-eyed hero believes Earth Ponies, Pegasi and Unicorns should be pals — and, hoof to heart, she’s determined to prove it.
7s8MovieSankofaHaile GerimaKofi Ghanaba, Oyafunmike Ogunlano, Alexandra Duah, Nick Medley, Mutabaruka, Afemo Omilami, Reggie Carter, MzuriUnited States, Ghana, Burkina Faso, United Kingdom, Germany, EthiopiaSeptember 24, 20211993TV-MA125 minDramas, Independent Movies, International MoviesOn a photo shoot in Ghana, an American model slips back in time, becomes enslaved on a plantation and bears witness to the agony of her ancestral past.
8s9TV ShowThe Great British Baking ShowAndy DevonshireMel Giedroyc, Sue Perkins, Mary Berry, Paul HollywoodUnited KingdomSeptember 24, 20212021TV-149 SeasonsBritish TV Shows, Reality TVA talented batch of amateur bakers face off in a 10-week competition, whipping up their best dishes in the hopes of being named the U.K.'s best.
9s10MovieThe StarlingTheodore MelfiMelissa McCarthy, Chris O'Dowd, Kevin Kline, Timothy Olyphant, Daveed Diggs, Skyler Gisondo, Laura Harrier, Rosalind Chao, Kimberly Quinn, Loretta Devine, Ravi KapoorUnited StatesSeptember 24, 20212021PG-13104 minComedies, DramasA woman adjusting to life after a loss contends with a feisty bird that's taken over her garden — and a husband who's struggling to find a way forward.
show_idtypetitledirectorcastcountrydate_addedrelease_yearratingdurationlisted_indescription
8799s8798TV ShowZak StormNaNMichael Johnston, Jessica Gee-George, Christine Marie Cabanos, Christopher Smith, Max Mittelman, Reba Buhr, Kyle HebertUnited States, France, South Korea, IndonesiaSeptember 13, 20182016TV-Y73 SeasonsKids' TVTeen surfer Zak Storm is mysteriously transported to the Bermuda Triangle, where he becomes the captain of a magical ship full of misfits.
8800s8799MovieZed PlusChandra Prakash DwivediAdil Hussain, Mona Singh, K.K. Raina, Sanjay Mishra, Anil Rastogi, Ravi Jhankal, Kulbhushan Kharbanda, Ekavali Khanna, Mukesh Tiwari, Vinod AcharyaIndiaDecember 31, 20192014TV-MA131 minComedies, Dramas, International MoviesA philandering small-town mechanic's political ambitions are sparked when the visiting prime minister mistakenly grants him special security clearance.
8801s8800MovieZendaAvadhoot GupteSantosh Juvekar, Siddharth Chandekar, Sachit Patil, Chinmay Mandlekar, Rajesh Shringarpure, Pushkar Shrotri, Tejashree Pradhan, Neha JoshiIndiaFebruary 15, 20182009TV-14120 minDramas, International MoviesA change in the leadership of a political party sparks bitter conflict and the party's division into two rival factions.
8802s8801TV ShowZindagi Gulzar HaiNaNSanam Saeed, Fawad Khan, Ayesha Omer, Mehreen Raheel, Sheheryar Munawar, Samina Peerzada, Waseem Abbas, Javed Sheikh, Hina Khawaja BayatPakistanDecember 15, 20162012TV-PG1 SeasonInternational TV Shows, Romantic TV Shows, TV DramasStrong-willed, middle-class Kashaf and carefree, wealthy Zaroon meet in college, but before love can take root, they each have some growing up to do.
8803s8802MovieZinzanaMajid Al AnsariAli Suliman, Saleh Bakri, Yasa, Ali Al-Jabri, Mansoor Alfeeli, AhdUnited Arab Emirates, JordanMarch 9, 20162015TV-MA96 minDramas, International Movies, ThrillersRecovering alcoholic Talal wakes up inside a small-town police station cell, where he's subject to the mind games of a psychotic sadist.
8804s8803MovieZodiacDavid FincherMark Ruffalo, Jake Gyllenhaal, Robert Downey Jr., Anthony Edwards, Brian Cox, Elias Koteas, Donal Logue, John Carroll Lynch, Dermot Mulroney, Chloë SevignyUnited StatesNovember 20, 20192007R158 minCult Movies, Dramas, ThrillersA political cartoonist, a crime reporter and a pair of cops investigate San Francisco's infamous Zodiac Killer in this thriller based on a true story.
8805s8804TV ShowZombie DumbNaNNaNNaNJuly 1, 20192018TV-Y72 SeasonsKids' TV, Korean TV Shows, TV ComediesWhile living alone in a spooky town, a young girl befriends a motley crew of zombie children with diverse personalities.
8806s8805MovieZombielandRuben FleischerJesse Eisenberg, Woody Harrelson, Emma Stone, Abigail Breslin, Amber Heard, Bill Murray, Derek GrafUnited StatesNovember 1, 20192009R88 minComedies, Horror MoviesLooking to survive in a world taken over by zombies, a dorky college student teams with an urban roughneck and a pair of grifter sisters.
8807s8806MovieZoomPeter HewittTim Allen, Courteney Cox, Chevy Chase, Kate Mara, Ryan Newman, Michael Cassidy, Spencer Breslin, Rip Torn, Kevin ZegersUnited StatesJanuary 11, 20202006PG88 minChildren & Family Movies, ComediesDragged from civilian life, a former superhero must train a new crop of youthful saviors when the military preps for an attack by a familiar villain.
8808s8807MovieZubaanMozez SinghVicky Kaushal, Sarah-Jane Dias, Raaghav Chanana, Manish Chaudhary, Meghna Malik, Malkeet Rauni, Anita Shabdish, Chittaranjan TripathyIndiaMarch 2, 20192015TV-14111 minDramas, International Movies, Music & MusicalsA scrappy but poor boy worms his way into a tycoon's dysfunctional family, while facing his fear of music and the truth about his past.